Photovoltaic power plant energy harvest optimization - capacity factor, delta-p loss and ramp rate compensation

ABSTRACT

A method of controlling a renewable energy power plant is provided. The method includes retrieving output power measurement values for each inverter of a total number of inverters from a plurality of sensors provided at a location proximal to each inverter and retrieving a point of interconnection (POI) output measurement value for the renewable energy power plant based on a plurality of ON inverters of the total number of inverters. The method also includes calculating a POI measured setpoint for the renewable energy power plant based on a difference between a power reference value for the renewable energy power plant and the retrieved POI output measurement value for the renewable energy power plant, assigning a setpoint to each of the ON inverters and classifying each ON inverter as either a TRACKING ON inverter or a NON-TRACKING ON inverter based on whether each ON inverter is tracking at the setpoint.

RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 63/052,829, filed Jul. 16, 2020, entitled “Photovoltaic Power PlantEnergy Harvest Optimization-Capacity Factor, Dynamic Delta P and RampRate Compensation,” which is incorporated herein by reference in itsentirety for all that it teaches and for all purposes.

FIELD OF THE INVENTION

Embodiments of the present disclosure relate to systems and methods forreal-time processing of data and more particularly to systems andmethods for optimizing photovoltaic power plants.

BACKGROUND

Commercial and utility-scale photovoltaic (“PV”) power systems andplants generally organize solar panels into an array of PV strings.Typically, each string in the array contains the same number of solarpanels, connected in series, as all other PV strings in the same systemto produce the rated DC operating voltage. The PV strings are connectedin parallel to produce the current necessary for efficient DC to ACconversion given the rated capacity of inverters used in the DC to ACconversion process which is suitable for coupling to a power grid at apoint of interconnection (POI).

PV power plants require a significant initial investment and ongoingmaintenance effort in order to meet their performance expectations overthe lifetime of the plant. Accordingly, it is important to accuratelyand chronologically monitor key parameters of the PV power plant toevaluate the performance of the PV power plant. By monitoring PV powerplants, component failures and losses caused by factors that negativelyaffect the efficiency of the PV power plant, such as snow accumulationand soiling of solar panels, for example, may be identified andcorrected. The output of the PV power plant at the POI, such as voltage,reactive power, real power, and power factor are controlled to be withina range of specific values to meet requirements. PV power plants,however, undergo periods of intermittent production when for example,there is limited fuel (i.e., irradiance) supplied to the power plant.During these periods of intermittent production, the power plantproduces less than the nameplate capacity (e.g., rated capacity, nominalcapacity, installed capacity, or maximum effect) which is the maximumrated output of the inverter for the power plant under specificconditions designated by the manufacturer.

Knowing with certainty the maximum power curve (i.e., potentialinstantaneous output) for the entire power plant is an exercise indiminishing returns for owners/manufacturers of the power plant as wellas for purchasers of the renewable energy provided by the power plant.At best, what is known are measured readings at a few points, but onecannot take these few points to determine the potential instantaneousoutput. That would require integrating all the irradiance at any giventime. For example, there are added costs associated with investments inproviding additional equipment such as sensors and in allocating time toperforming tests which are required to determine the maximum powercurve. Compounding this uncertainty are power plant controllers that areresponsible for controlling the flow of power, active power (the actualpower dissipated in the system) and reactive (useless power which cyclesbetween the source, i.e., the power plant and the sink, i.e., the grid),through the POI. It is typical for there to be requirements related topower rate (the rate at which the power from the power plant can change)and power limit (the maximum power output by the power plant), whichsets constrained boundary conditions for the PV power plant.

The boundary conditions are a combination of limits that are imposed byphysical (e.g. equipment ratings, mechanical limits, weather) andeconomic (e.g. grid stability, price, power purchase agreements, time ofuse) constraints. It is typical to size a power plant, within a veryapproximate range of 10-20 percent, larger than the intended maximum,active power output limit. This is strategic and ultimately allowsinverters to operate as low as 80% capacity on an ideal solar day. Thisextends and optimizes the inverter's useful life span, and allows amargin of error in generating the required energy, from the power plant,to meet contractual obligations. With the additional capacity, the powerplant's maximum available power curve may be above the contractualmaximum power limit. Thus, a boundary condition is formed by this powerlimit. In order to maintain the frequency on the grid at 60 Hz, thepower injected into the grid, “Pi”, and power dissipated from the grid,“Po”, always need to be equal. Given the unpredictability of fuel,(i.e., the irradiance) in the PV plant context, Pi becomes unpredictableas more PV plants are connected to the grid. When this happens, the gridfrequency tends to slow, with a sudden loss in demand, a reduction inPo, the frequency tends to increase. Conventionally, inertial dampeningand speed governing systems stem the initial droop in time for peakingplants to increase or decrease output to meet demand. However, asrenewable penetrations continue and accelerate, the percentage ofinertia storing generators on the grid will decline and a need for afast reacting, local frequency response will become commonplace. Thereare mechanisms known for adjusting the frequency of the grid that helpto balance the equation. By requiring PV power plants to predictablyramp their power up and down at certain rates, a defensive strategy,positive, if available, and negative power reserve can be used inresponse to the change in frequency on the grid at any given time. Thus,a POI rate limit is formed where the POI rate limit is defined as themaximum increase or decrease in power per unit time allowed at the POI.

These physical and economic constraints make it difficult to generate amaximum power curve which conforms to the purchaser's power qualityrequirements while not sacrificing energy, which theowners/manufacturers have a vested interest in preserving. When there isan uncertain irradiance gradient across a PV solar panel, typicalcontrol methods cause losses to accrue in a way that is not proportionalto the available irradiance for an individual array of PV strings. Forinverters that are unconstrained from a fuel perspective but constrainedby a power limit, compensation techniques are essential for allowing apower plant to produce near an optimal power curve (a cure that followsthe power rate requirements and does not exceed the power limitrequirements) under varying resource availability, especially for rateand limit constrained power systems. As renewable power grid penetrationincreases and spinning reserve (the amount of unused capacity which cancompensate for power shortages or frequency drops within a given periodof time) decreases, dispatchable renewable power plants which mustoperate with rate and limit constraints will not only become more commonbut will become widely necessary. Compensation will improveprofitability for owners/manufacturers while providing better and morepredictable power to purchasers.

Thus, there is a need for a system and method that can harvestadditional energy from a PV power plant while providing a smooth andpredictable supply of power from the PV power plant to the utility gridby compensating for losses.

SUMMARY OF THE INVENTION

In accordance with the present disclosure, a PV plant compensationsystem and method are provided that require considerably less hardwarethan existing systems. Additionally, the system and method describedherein can be employed to determine which inverters are operating andwhich inverters are not operating. After determining which inverters areoperating and which inverters are not operating, the system and methoddetermines which of the operating inverters have a power output whichmatches a predetermined setpoint (TRACKING ON inverters) and which ofthe operating inverters have a power output that does not match thepredetermined setpoint (NON-TRACKING ON inverters). For the operatinginverters that have a power output that does not match the predeterminedsetpoint (NON-TRACKING ON inverters), the power output is increaseduntil it matches the predetermined setpoint.

The present disclosure provides a number of advantages depending on theparticular aspect, embodiment, and/or configuration. Althoughembodiments of the present disclosure are directed to solar energy,other forms of renewable energy such as wind energy, hydropower energy,geothermal energy, hydroelectric energy, hydrogen energy, bioenergy,etc. can be used without departing from the spirit and scope of thepresent disclosure. For example, methods and systems according toembodiments of the present disclosure can generally be applied torenewable energy systems (e.g., power plants) when the followingconditions are met: (1) a renewable energy power plant where the totalrated capacity of the renewable energy power plant is made up of anaggregation of generators (inverters) with smaller capacities and theaggregate output is conjoined at a POI; (2) the inverters' availability(ON) and fuel levels (i.e. sun, wind, water, heat, etc.) can beuncertain; and (3) there are rate and or output limitations imposed bythe interconnection agreement with the utility company.

Embodiments include a method of controlling a renewable energy powerplant. The method includes retrieving a sum of output power measurementvalues for each inverter of a total number of inverters from a pluralityof sensors, with each sensor provided at a location proximal to eachinverter and retrieving a point of interconnection (POI) outputmeasurement value for the renewable energy power plant based on aplurality of ON inverters of the total number of inverters. The methodalso includes calculating a POI measured setpoint for the renewableenergy power plant based on a difference between a power reference valuefor the renewable energy power plant and the retrieved POI outputmeasurement value for the renewable energy power plant and calculating asummation of output power measurement values for the ON inverters basedon a capacity factor for the ON inverters. The method further includescalculating a setpoint for the renewable energy power plant, assigningthe setpoint to each of the ON inverters and classifying each ONinverter as either a TRACKING ON inverter or a NON-TRACKING ON inverterbased on whether each ON inverter is tracking at the setpoint.

Aspects of the above method include increasing the setpoint in responseto detecting the summation of output power measurements from each of theON inverters is less than the setpoint.

Aspects of the above method include calculating a loss value for theTRACKING ON inverters, calculating a deviation percentage from the lossvalue and adding the deviation percentage to the setpoint for theTRACKING ON inverters to generate an adjusted setpoint.

Aspects of the above method include applying the adjusted setpoint tothe TRACKING ON inverters until at least one of: the TRACKING ONinverters are no longer tracking and become NON-TRACKING ON inverters,the TRACKING ON inverters are outputting at their rated capacity, andthe power reference value for the renewable energy power plant has beenreached.

Aspects of the above method include the POI output measurement value isretrieved from a meter provided between the renewable energy power plantand a power grid.

Aspects of the above method include correcting the setpoint for theNON-TRACKING ON inverters and adding a rate limited setpoint increase tothe NON-TRACKING ON inverters.

Aspects of the above method include the rate limited setpoint increaseis inversely proportional to a number of NON-TRACKING ON inverters.

Embodiments include a renewable energy power plant controller. Therenewable energy power plant controller comprising a processor andmemory device and the renewable energy power plant controller isconfigured to retrieve a sum of output power measurement values for eachinverter of a total number of inverters from a plurality of sensors,with each sensor provided at a location proximal to each inverter,retrieve a point of interconnection (POI) output measurement value for arenewable energy power plant based on a plurality of ON inverters of thetotal number of inverters, calculate a POI measured setpoint for therenewable energy power plant based on a difference between a powerreference value for the renewable energy power plant and the retrievedPOI output measurement value for the renewable energy power plant,calculate a summation of output power measurement values for the ONinverters based on a capacity factor for the ON inverters, calculate asetpoint for the renewable energy power plant, assign the setpoint toeach of the ON inverters and classify each ON inverter as either aTRACKING ON inverter or a NON-TRACKING ON inverter based on whether eachON inverter is tracking at the setpoint

Aspects of the above renewable energy power plant controller include therenewable energy power plant controller further configured to increasethe setpoint in response to detecting the summation of output powermeasurements from each of the ON inverters is less than the setpoint.

Aspects of the above renewable energy power plant controller include therenewable energy power plant controller further configured to calculatea loss value for the TRACKING ON inverters, calculate a deviationpercentage from the loss value and add the deviation percentage to thesetpoint for the TRACKING ON inverters to generate an adjusted setpoint.

Aspects of the above renewable energy power plant controller include therenewable energy power plant controller further configured to apply theadjusted setpoint to the TRACKING ON inverters until at least one of:the TRACKING ON inverters are no longer tracking and become NON-TRACKINGON inverters, the TRACKING ON inverters are outputting at their ratedcapacity, and the power reference value for the renewable energy powerplant has been reached Aspects of the above renewable energy power plantcontroller include the POI output measurement value is retrieved from ameter provided between the renewable energy power plant and a powergrid.

Aspects of the above renewable energy power plant controller include therenewable energy power plant controller further configured to correctthe setpoint for the NON-TRACKING ON inverters and add a rate limitedsetpoint increase to the NON-TRACKING ON inverters.

Aspects of the above renewable energy power plant controller includewherein the rate limited setpoint increase is inversely proportional toa number of NON-TRACKING ON inverters.

Embodiments include one or more non-transitory computer-readable storagemedia having computer-executable instructions embodied thereon forcontrolling a plurality of renewable energy inverters, wherein whenexecuted by a renewable energy power plant controller, thecomputer-executable instructions cause the renewable energy power plantcontroller to retrieve a sum of output power measurement values for eachinverter of a total number of inverters from a plurality of sensors,with each sensor provided at a location proximal to each inverter,retrieve, from an electric meter, a point of interconnection (POI)output measurement value for a renewable energy power plant based on aplurality of ON inverters of the total number of inverters, calculate aPOI measured setpoint for the renewable energy power plant based on adifference between a power reference value for the renewable energypower plant and the retrieved POI output measurement value for therenewable energy power plant, calculate a summation of output powermeasurement values for the ON inverters based on a capacity factor forthe ON inverters, calculate a setpoint for the renewable energy powerplant, assign the setpoint to each of the ON inverters and classify eachON inverter as either a TRACKING ON inverter or a NON-TRACKING ONinverter based on whether each ON inverter is tracking at the setpoint.

Aspects of the above computer-readable storage media include wherein thecomputer-executable instructions also cause the renewable energy powerplant controller to increase the setpoint in response to detecting thesummation of output power measurements from each of the ON inverters isless than the setpoint.

Aspects of the above computer-readable storage media include wherein thecomputer-executable instructions also cause the renewable energy powerplant controller to calculate a loss value for the TRACKING ONinverters, calculate a deviation percentage from the loss value and addthe deviation percentage to the setpoint for the TRACKING ON invertersto generate an adjusted setpoint.

Aspects of the above computer-readable storage media include wherein thecomputer-executable instructions also cause the renewable energy powerplant controller to apply the adjusted setpoint to the TRACKING ONinverters antis at least one of: the TRACKING ON inverters are no longertracking and become NON-TRACKING ON inverters, the TRACKING ON invertersare outputting at their rated capacity, and the power reference valuefor the renewable energy power plant has been reached.

Aspects of the above computer-readable storage media include wherein thecomputer-executable instructions also cause the renewable energy powerplant controller to correct the setpoint for the NON-TRACKING ONinverters and add a rate limited setpoint increase to the NON-TRACKINGON inverters.

Aspects of the above computer-readable storage media include wherein therate limited setpoint increase is inversely proportional to a number ofNON-TRACKING ON inverters.

References made herein to “photovoltaic arrays,” “photovoltaic systems,”“photovoltaic modules,” or “solar panels,” should not necessarily beconstrued as limiting the present disclosure to a particular type ofsolar power plant. It will be recognized by one skilled in the art thatthe present disclosure may be used to analyze and classify losses forany type of solar power plant, including concentrating solar powersystems and solar thermal power systems.

The phrases “at least one”, “one or more”, and “and/or”, as used herein,are open-ended expressions that are both conjunctive and disjunctive inoperation. For example, each of the expressions “at least one of A, Band C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “oneor more of A, B, or C” and “A, B, and/or C” means A alone, B alone, Calone, A and B together, A and C together, B and C together, or A, B andC together.

The term “a” or “an” entity, as used herein, refers to one or more ofthat entity. As such, the terms “a” (or “an”), “one or more” and “atleast one” can be used interchangeably herein. It is also to be notedthat the terms “comprising”, “including”, and “having” can be usedinterchangeably.

The term “automatic” and variations thereof, as used herein, refers toany process or operation done without material human input when theprocess or operation is performed. However, a process or operation canbe automatic, even though performance of the process or operation usesmaterial or immaterial human input, if the input is received beforeperformance of the process or operation. Human input is deemed to bematerial if such input influences how the process or operation will beperformed. Human input that consents to the performance of the processor operation is not deemed to be “material”.

The term “computer-readable medium,” as used herein, refers to anytangible storage and/or transmission medium that participates inproviding instructions to a processor for execution. Such a medium maytake many forms, including but not limited to, non-volatile media,volatile media, and transmission media. Non-volatile media includes, forexample, non-volatile random access memory (NVRAM), or magnetic oroptical disks. Volatile media includes dynamic memory, such as mainmemory. Common forms of computer-readable media include, for example, afloppy disk, a flexible disk, hard disk, magnetic tape, or any othermagnetic medium, magneto-optical medium, a compact disc read only memory(CD-ROM), any other optical medium, punch cards, paper tape, any otherphysical medium with patterns of holes, a random access memory (RAM), aprogrammable read only memory (PROM), and erasable programmable readonly memory EPROM, a FLASH-EPROM, a solid state medium like a memorycard, any other memory chip or cartridge, a carrier wave as describedhereinafter, or any other medium from which a computer can read. Adigital file attachment to an e-mail or other self-contained informationarchive or set of archives is considered a distribution mediumequivalent to a tangible storage medium. When the computer-readablemedia is configured as a database, it is to be understood that thedatabase may be any type of database, such as relational, hierarchical,object-oriented, and/or the like. Accordingly, the present disclosure isconsidered to include a tangible storage medium or distribution mediumand prior art-recognized equivalents and successor media, in which thesoftware implementations of the present disclosure are stored. It shouldbe noted that any computer readable medium that is not a signaltransmission may be considered non-transitory.

The term “desktop,” as used herein, refers to a metaphor used to portraysystems. A desktop typically includes pictures, called icons, that showapplications, windows, cabinets, files, folders, documents, and othergraphical items. The icons are generally selectable through userinterface interaction to allow a user to execute applications or conductother operations.

The term “display”, as used herein, refers to a portion of a displayimage used to display the output of a computer to a user.

The term “displayed image”, as used herein, refers to an image producedon the display. A typical displayed image is a window or desktop. Thedisplayed image may occupy all or a portion of the display.

The term “module,” as used herein, refers to any known or laterdeveloped hardware, software, computer readable medium, firmware,artificial intelligence, fuzzy logic, or combination of hardware andsoftware with functionality associated with a particular task and thatis capable of performing the functionality associated with that task.

The term “window”, as used herein, refers to a, typically rectangular,displayed image on part of a display that contains or provides contentdifferent from the rest of the screen.

The terms “determine”, “calculate” and “compute,” and variationsthereof, as used herein, are used interchangeably and include any typeof methodology, process, mathematical operation or technique.

It shall be understood that the term “means” as used herein shall begiven its broadest possible interpretation in accordance with 35 U.S.C.,Section 112, Paragraph 6. Accordingly, a claim incorporating the term“means” shall cover all structures, materials, or acts set forth herein,and all of the equivalents thereof. Further, the structures, materialsor acts and the equivalents thereof shall include all those described inthe summary of the present disclosure, brief description of thedrawings, detailed description, abstract, and claims themselves.

The preceding is a simplified summary of the present disclosure toprovide an understanding of some aspects of the present disclosure. Thissummary is neither an extensive nor exhaustive overview of the presentdisclosure and its various aspects, embodiments, and/or configurations.It is intended neither to identify key or critical elements of thepresent disclosure nor to delineate the scope of the present disclosurebut to describe selected concepts of the present disclosure in asimplified form as an introduction to the more detailed descriptionpresented below. As will be appreciated, other aspects, embodiments,and/or configurations of the present disclosure are possible utilizing,alone or in combination, one or more of the features set forth above ordescribed in detail below.

Other features and advantages of the present disclosure will becomeapparent from a review of the following detailed description, taken inconjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example communications/data processing network system thatmay be used in conjunction with embodiments of the present disclosure;

FIG. 2 is an example data processing system that may be used inconjunction with embodiments of the present disclosure;

FIG. 3A is a block diagram illustrating components of a photovoltaic(PV) power plant in conjunction with a compensation system in accordancewith an embodiment of the present disclosure;

FIG. 3B is a block diagram illustrating additional components of the PVpower plant in conjunction with a compensation system of FIG. 3A inaccordance with an embodiment of the present disclosure;

FIG. 4 is a block diagram of an embodiment of the compensation systemaccording to the present disclosure;

FIGS. 5A-5C is a flowchart of an embodiment of a compensation methodaccording to the present disclosure;

FIG. 6 is a block diagram of an embodiment of a capacity factor moduleaccording to the present disclosure;

FIG. 7 is a block diagram of an embodiment of a PV plant moduleaccording to the present disclosure;

FIG. 8 is a block diagram of an embodiment of a PV compensation moduleaccording to the present disclosure; and

FIG. 9 is a block diagram of an embodiment of a PV unit module accordingto the present disclosure.

In the appended figures, similar components and/or features may have thesame reference label. Further, various components of the same type maybe distinguished by following the reference label by a letter thatdistinguishes among the similar components. If only the first referencelabel is used in the specification, the description is applicable to anyone of the similar components having the same first reference labelirrespective of the second reference label.

DETAILED DESCRIPTION

The following detailed description describes one or more embodiments ofthe disclosed system and method. First, the detailed descriptionprovides a description of a network system and a computer system thatmay be used in connection with the compensation system and methoddisclosed herein. The detailed description then provides a disclosure ofembodiments of the compensation system and method disclosed herein. Thedetailed description further provides various user interfaces or outputsgenerated by the compensation system and method disclosed herein.

Referring to FIG. 1, an example network system is provided that may beused in connection with the compensation system and method disclosedherein. More specifically, FIG. 1 illustrates a block diagram of asystem 100 that may use a compensation system to compensation for thelosses of PV power plant. The system 100 includes one or more dataprocessors, such as user computers 105, 110, and 115. The user computers105, 110, and 115 may be general purpose personal computers (including,merely by way of example, personal computers and/or laptop computersrunning various versions of Microsoft Corp.'s Windows™ and/or AppleCorp.'s Macintosh™ operating systems) and/or workstation computersrunning any of a variety of commercially-available UNIX™ or UNIX-likeoperating systems. These user computers 105, 110, 115 may also have anyof a variety of applications, including for example, database clientand/or server applications, and web browser applications. Alternatively,the user computers 105, 110, and 115 may be any other electronic device,such as a thin-client computer, internet-enabled mobile telephone,and/or personal digital assistant, capable of communicating via anetwork (e.g., the network 120 described below) and/or displaying andnavigating web pages or other types of electronic documents. Althoughthe exemplary system 100 is shown with three user computers, any numberof user computers may be supported.

System 100 further includes a network 120. The network 120 may be anytype of network familiar to those skilled in the art that can supportdata communications using any of a variety of commercially-availableprotocols, including without limitation TCP/IP, SNA, IPX, AppleTalk, andthe like. Merely by way of example, the network 120 may be a local areanetwork (“LAN”), such as an Ethernet network, a Token-Ring networkand/or the like; a wide-area network; a virtual network, includingwithout limitation a virtual private network (“VPN”); the Internet; anintranet; an extranet; a public switched telephone network (“PSTN”); aninfra-red network; a wireless network (e.g., a network operating underany of the IEEE 802.11 suite of protocols, the Bluetooth™ protocol knownin the art, and/or any other wireless protocol); and/or any combinationof these and/or other networks.

The system may also include one or more server computers 125, 130. Oneserver may be a web server 125, which may be used to process requestsfor web pages or other electronic documents from user computers 105,110, and 120. The web server can be running an operating systemincluding any of those discussed above, as well as anycommercially-available server operating systems. The web server 125 canalso run a variety of server applications, including HTTP servers, FTPservers, CGI servers, database servers, Java servers, and the like. Insome instances, the web server 125 may publish operations available asone or more web services.

The system 100 may also include one or more file and/or applicationservers 130, which can, in addition to an operating system, include oneor more applications accessible by a client running on one or more ofthe user computers 105, 110, 115. The server(s) 130 may be one or moregeneral purpose computers capable of executing programs or scripts inresponse to the user computers 105, 110 and 115. As one example, theserver may execute one or more web applications. The web application maybe implemented as one or more scripts or programs written in anyprogramming language, such as Java™, C, C #™ or C++, and/or anyscripting language, such as Perl, Python, or TCL, as well ascombinations of any programming/scripting languages. The applicationserver(s) 130 may also include database servers, including withoutlimitation those commercially available from Oracle, Microsoft, Sybase™,IBM™ and the like, which can process requests from database clientsrunning on a user computer 105.

In some embodiments, an application server 130 may create web pagesdynamically for displaying information and reports generated by thecompensation system. The web pages created by the web application server130 may be forwarded to a user computer 105 via a web server 125.Similarly, the web server 125 may be able to receive web page requests,web services invocations, and/or input data from a user computer 105 andcan forward the web page requests and/or input data to the webapplication server 130.

In further embodiments, the server 130 may function as a file server.Although for ease of description, FIG. 1 illustrates a separate webserver 125 and file/application server 130, those skilled in the artwill recognize that the functions described with respect to servers 125,130 may be performed by a single server and/or a plurality ofspecialized servers, depending on implementation-specific needs andparameters.

The system 100 may also include a database 135. The database 135 mayreside in a variety of locations. By way of example, database 135 mayreside on a storage medium local to (and/or resident in) one or more ofthe computers 105, 110, 115, 125, 130. Alternatively, it may be remotefrom any or all of the computers 105, 110, 115, 125, 130, and incommunication (e.g., via the network 120) with one or more of these. Ina particular set of embodiments, the database 135 may reside in astorage-area network (“SAN”) familiar to those skilled in the art.Similarly, any necessary files for performing the functions attributedto the computers 105, 110, 115, 125, 130 may be stored locally on therespective computer and/or remotely, as appropriate. In one set ofembodiments, the database 135 may be a relational database, such asOracle 10I™, that is adapted to store, update, and retrieve data inresponse to SQL-formatted commands.

Referring to FIG. 2, an example data-processing system is provided thatmay be used in connection with the compensation system and methoddisclosed herein. More specifically, FIG. 2 illustrates one embodimentof a data-processing system 200 upon which the compensation system orcomponents of a compensation system may be deployed or executed. Thedata-processing system 200 is shown comprising hardware elements thatmay be electrically coupled via a bus 255. The hardware elements mayinclude one or more central processing units (CPUs) 205; one or moreinput devices 210 (e.g., a mouse, a keyboard, etc.); and one or moreoutput devices 215 (e.g., a display device, a printer, etc.). Thedata-processing system 200 may also include one or more storage devices220. By way of example, storage device(s) 220 may be disk drives,optical storage devices, solid-state storage device such as a randomaccess memory (“RAM”) and/or a read-only memory (“ROM”), which can beprogrammable, flash-updateable and/or the like.

The data-processing system 200 may additionally include acomputer-readable storage media reader 225; a communications system 230(e.g., a modem, a network card (wireless or wired), an infra-redcommunication device, etc.); and working memory 240, which may includeRAM and ROM devices as described above. In some embodiments, thedata-processing system 200 may also include a processing accelerationunit 235, which can include a DSP, a special-purpose processor and/orthe like.

The computer-readable storage media reader 225 can further be connectedto a computer-readable storage medium, together (and, optionally, incombination with storage device(s) 220) comprehensively representingremote, local, fixed, and/or removable storage devices plus storagemedia for temporarily and/or more permanently containingcomputer-readable information. The communications system 230 may permitdata to be exchanged with the network 120 and/or any otherdata-processing described above with respect to the system 100.

The data-processing system 200 may also comprise software elements,shown as being currently located within the working memory 240,including an operating system 245 and/or other code 250, such as programcode implementing a compensation system or components of a compensationsystem. It should be appreciated that alternate embodiments of adata-processing system 200 may have numerous variations from thatdescribed above. For example, customized hardware might also be usedand/or particular elements might be implemented in hardware, software(including portable software, such as applets), or both. Further,connection to other computing devices such as network input/outputdevices may be employed.

FIG. 3A is a block diagram illustrating components of a PV power plantin conjunction with a compensation system in accordance with anembodiment of the present disclosure. The PV power plant 300 includes aplurality of PV strings 304, 308, 312, 316, 320, 324, a plurality ofcombiners 328, 332, 336 and an inverter 352. Each PV string consists ofindividual solar panels, typically eight to twelve panels, wired inseries. The output signals of the PV strings are wired, in parallel,into the combiners 328, 332, 336. Each combiner can receive outputsignals from one or more PV string. For example, in FIG. 3A, PV String1304 through PV String n 308 are wired into combiner 1328, PV String1312 through PV String n 316 are wired into combiner 2332, and PV String1320 through PV String n 324 are wired into combiner 3336. Each combinersums the power signals of their PV strings, thereby providing acumulative direct current (“DC”) power output that is associated with aplurality of PV strings. The output signals of combiners 328, 332, 336are wired into the inverter 352. In FIG. 3A, only one inverter isillustrated. However, in large PV power plants, multiple inverters areemployed, each accepting output signals of multiple combiners. Theinverter 352 converts the DC power of the solar panels into three phasealternating current (“AC”) power which ultimately can be used bycommercial power plants.

As illustrated in FIG. 3A, measurement hardware, such as sensors 340,344, 348, detect the input signals of the inverters 352. In addition,measurement hardware includes sensors 350 that detects the outputsignals for each inverter 352. The sensors may be separate from theinverter 352, or the sensors may be incorporated into the inverter 352.Optionally, measurement hardware, such as sensors 340, 344, 348, canmeasure the output of each individual string 304-324 instead of theoutput of combiners 328, 332, 336. The choice of how many strings304-324 each sensor measures is a tradeoff between the cost of thesensors required and the signal to noise ratio for detecting a singlestring failure.

By locating the sensors near the inverter 352, the hardware costs, suchas the quantity of sensors and associated wiring, is significantlyreduced. This is especially important for large PV systems wherethousands of strings are employed. Each sensor 340, 344, 348. 350 andthe individual data entries detected by the sensor, is associated with adata channel. As shown in FIG. 3A, sensor 1340 is associated with afirst data channel 364, sensor 2344 is associated with a second datachannel 368, sensor 3348 is associated with a third data channel 372,and sensor 4 350 is associated with a fourth data channel 376. Each datachannel is associated with the individual data entries detected by therespective sensors.

To further reduce hardware costs, in at least one embodiment, eachcombiner sums the output of at least six PV strings, and preferably, atleast twelve PV strings. This reduces the number of combiners requiredin a PV power plant, as well as reducing the number of sensors andassociated wiring required to monitor the performance of the PV powerplant. Accordingly, each sensor detects data that is associated with aplurality of PV strings. This data is collected and analyzed by thecompensation system 400 to analyze and compensate for losses of the PVpower plant 300.

In the ideal case, the signal to noise level can be defined as 1/n,where n is the number of strings in a group. For example, with tenstrings per group, a single string failure would result in a ten percentreduction in current at the inverter input. However, the ideal case isnot achievable because the signal-to-noise ratio is further reduced dueto measurement errors, differences between solar panels, mounting, andenvironmental conditions such as cloud shading, soiling (dirt on thepanels), and obstructions. Embodiments of the compensation system andmethod utilize a number of approaches to compensate for these noiseissues, thus enabling the detection of single string failures orperformance degradation from a data channel associated with a pluralityof PV strings.

Referring back to FIG. 3A, the sensors 340, 344, 348, 350 are incommunication with a transceiver 360, which transmits the sensor datathrough the network 120 to the compensation system 400. The sensor datamay be at least one of current and voltage data. Examples of sensorsinclude, but are not limited to, voltage transformers (VT), currenttransformers (CT), and Hall Effect sensors. As shown in FIG. 3A, eachsensor 340, 344, 348, is associated with an output signal of a combiner,which is the summation of a plurality of PV strings. Sensor 350 isassociated with an output signal of the inverter 352. Accordingly, thesensor data that is transmitted to the compensation system 400 isassociated with a plurality of PV strings and inverters.

FIG. 3B is a block diagram illustrating additional components of the PVpower plant 300 in conjunction with a compensation system 400 of FIG. 3Ain accordance with an embodiment of the present disclosure. FIG. 3Bshows the inverters 352, sensors 350, transceivers 360 and thecompensation system 400 described in connection with FIG. 3A. Thestrings, combiners, sensors 1-3 and network 120 are not shown in FIG. 3Bfor clarity of illustration. The PV power plant 300 is coupled to autility power grid 356 at a point of interconnection (POI) 354. In theexample of FIG. 3B, the output of a group of inverters 352 are coupledto the POI 354 by way of a medium voltage (MV) feeder 380 to asubstation MV/HV (medium voltage/high voltage) transformer 384. Thereare several groups of inverters 352 in the PV power plant 300, with eachgroup of inverters 352 being connected to its own MV feeder 380. Theinverters 352 are typically located in inverter pads far from the POI354 with the utility power grid 356. Due to the impedance of the ACcollection system, the voltage and other outputs measured at terminalsof an inverter 352 are not the same as the voltage and other outputsmeasured at the POI 354. The operation of a plurality of inverters 352also needs to be coordinated to meet output requirements at the POI 354.

The compensation system 400 is configured to facilitate control of thePV power plant output (e.g., voltage) at or near the POI 354. In oneembodiment of the present disclosure, the compensation system 400controls setpoints of corresponding inverters 352 to achieve a desiredPV power plant output at the POI 354. More specifically, thecompensation system 400 may be configured to adjust a setpoint of aninverter(s) 352, the setpoint commanding the inverter 352 to generate aparticular output value as discussed in greater detail below.

The meter 353 may comprise a conventional electrical meter or othersensing element with data communication capability. The meter 353 maycomprise a root mean square (RMS) transmitter, revenue meter, protectiverelays, and other measurement/sensing apparatus. In the example of FIG.3B, the meter 353 measures the output of the PV power plant 300 at thePOI 354. This allows the meter 353 to have a reading of the PV powerplant output to compare with readings at the terminals of the inverters352 using sensors 350. Examples of PV power plant output measured by themeter 353 at the POI 354 include voltage, power factor, reactive power,and real power. In the example of FIG. 3B, the solid lines representelectrical power flow and the dash lines represent data flow. The dataflow may be in accordance with Supervisory Control and Data Acquisition(SCADA) control.

FIG. 4 illustrates an embodiment of the compensation system 400discussed above in connection with FIGS. 3A and 3B. As shown in FIG. 4,the compensation system 400 includes multiple servers and databases. Thenumber and configuration of the servers and databases are shown forillustration purposes only and may be altered without departing from thescope of the present disclosure. For example, a single server anddatabase may be utilized. As depicted in FIG. 4, a data server 408 is incommunication with the network 120 and receives sensor data from one ormore transceivers 360 . . . 360N associated with PV power plant 300.Optionally, the data server 408 may receive weather data 404. Theweather data 404 may originate from a weather substation located at eachof the PV power plant 300, and may include environmental conditions suchas solar radiance, wind speed, wind direction, temperature, rain, snow,and humidity. Optionally, weather data 404 may be obtained from multiplelocations within a PV power system 300 to detect and characterizeweather variations within the PV power plant 300. For example, PV powerplant 300 may include sensors that collect weather data 404 at eachstring or for all strings associated with a combiner. Measuring thesolar radiance, using a pyranometer, allows the compensation system 400to evaluate the impact of smog, haze, or clouds when determining anexpected power output for the PV power plant 300 using a model for thePV power plant 300.

The data server 408 communicates with a data database 412, which storessensor data 416, metadata 420, and calibration data 424 for the PV powerplant 300 being monitored. Sensor data 416 may be voltage data orcurrent data and may include instantaneous values as well astime-averaged data. The sensor data 416 may include information receivedfrom each sensor 340, 344, 348, 350 for the life of the PV power plant300. The sensor data also includes data from meter 353 which measuresthe output of the PV power plant 300 at the POI 354. Metadata 420includes data associated with the sensor data, such as weather data,timestamp, combiner identification, inverter identification, invertercapacity values and sensor identification. Calibration data 424 includesthe initial calibration data recorded when the PV power plant 300 wasfirst commissioned as well as periodic calibration data initiated by thecompensation system 400. The calibration data 424 is associated with thedata channels 364, 368, 372, 376 of the sensors 340, 344, 348, 350 ofeach PV power plant 300.

The data server 408 also communicates with a web server 428. The webserver 428 communicates with a user computer 105, a web application 432,and a preferences database 436. The web application 432 includes a userinterface that allows a user to monitor the performance of the PV powerplant 300, to set analysis conditions 440, and to set performancethresholds 444. The web application 432 may also generate userconfigurable display images or user interfaces to display information toa user.

According to one embodiment of the present disclosure, the analysisconditions 440 are intended to determine which of the inverters 352 areoperating in the “ON” state based on the sensor data from sensor 350.For example, this determination can be made based on performancethresholds 444 and the sensor data from sensor 350 to only recognizeinverters 352 that have an output power value above a particularthreshold. According to another embodiment of the present disclosure,the analysis conditions 444 may limit the analysis of the compensationsystem 400 to periods of time when each PV power plant 300 should beproducing at least a minimum amount of power. At low power levels,measurement and other errors represent a larger contribution to the datathan at higher power levels. Thus, by restricting the analysis to thosetimes when the string power is above a preset threshold, the reliabilityof the compensation system 400 is improved. Analysis conditions 440include the time of day the compensation system 400 will monitor theperformance of each PV power plant 300, the position of the sun,geometric interference shading data, a minimum solar irradiation level,a minimum current or voltage level, and a minimum power level.

Performance thresholds 444 are used to detect an underperforming PVstring and/or an underperforming inverter. Performance thresholds 444include a comparator and a deviation value. Comparators include aspecification performance comparator, a statistical average performancecomparator, a channel-to-channel comparator, and a time-differentialcomparator. A specification performance comparator comprises comparingthe actual performance of a plurality of PV strings and/or the PV arraywith the optimal performance of the strings and/or the PV system. Theoptimal performance, or expected output, of the PV strings and/or the PVsystem is determined by the compensation analysis engine 452. Likewise,the specification performance comparator also comprises comparing theactual performance of the inverters 352 with the optimal performance ofthe inverters 352 in the PV power plant 300. The optimal performance, orexpected output, of the inverters 352 is determined by the compensationanalysis engine 452 as discussed in greater detail below.

A statistical average performance comparator comprises comparing theactual performance of a plurality of PV strings and inverters with thestatistical average performance of the strings and inverters, which maybe determined during a testing phase of the PV power plant 300. Achannel-to-channel comparator comprises comparing the actual performanceof a plurality of PV strings and inverters with the actual performanceof another plurality of PV strings or inverters. In some embodiments, adata entry received by one data channel may be compared to a data entryreceived from multiple other data channels. Additionally, in someembodiments, the channel-to-channel comparator may compare data entriesassociated with similar sun positions, even if the data entries were notdetected at the same time or date. A time-differential comparatorcomprises comparing the actual performance of a plurality of PV stringsand/or inverter with the performance of the plurality of PV stringsand/or inverter at an earlier date. The time-differential comparatorcompares data entries associated with similar sun positions. Forexample, the time-differential comparator may compare a data entryassociated with a plurality of PV strings and/or inverters with a dataentry associated with the same plurality of PV strings and/or inverterbut detected one year earlier. Shorter-term comparisons, such as dailycomparisons, help the compensation system 400 quickly identify andclassify a failure or loss whereas longer-term comparisons, such asyearly comparisons, help the compensation system 400 identifyperformance degradation issues that are hard to detect in shorter-termcomparisons. A single performance threshold comparator, or anycombination thereof, may be utilized. In at least one embodiment, achannel-to-channel comparator and a time-differential comparator areutilized. The deviation value comprises a percentage variance that theactual performance can vary from the comparator value. The deviationvalue includes a predefined percentage, a standard deviation value, or aproduction impact.

The analysis conditions 440 and the performance thresholds 444 may beuser-selectable. In one configuration, the user may set the analysisconditions 440 and thresholds 444 via a web application 432. Duringdevelopment testing, a simulated run-time environment is provided thatcan execute the conditions and thresholds under a set of predefinedconditions. The simulations performed during development testing allowthe user to test, debug and perfect the analysis conditions andperformance thresholds before deployment. The simulated run-timeenvironment testing package is stored in a database for continueddevelopment and editing, thereby allowing a user to test new analysisconditions and performance thresholds before entering them into theproduction web servers. Accordingly, a user may set the compensationconditions and thresholds under which the compensation system 400 willanalyze the sensor data and monitor performance of a PV power plant 300.The conditions and thresholds may have predefined default values whichwill be used by the compensation system 400 until a user overrides thedefault values by entering a user-selectable value.

A compensation analysis server 448 is also provided in the compensationsystem 400. The compensation analysis server 448 communicates with thedata server 408, the web server 428, as well as the compensationanalysis engine 452 and the compensation analysis database 456. Thecompensation analysis database 456 stores the compensation analysis data460. In addition, the compensation analysis database 456 may include apower reference value for the PV power plant, a loss value Delta-P,setpoints, an adjusted capacity, a power limit, a power rate limit, arate limited setpoint increase, a capacity tracking value as well asother values discussed in greater detail below.

Referring now to FIGS. 5A-5C, an embodiment of a compensation method 500of the present disclosure is illustrated. While a general order for thesteps of the method 500 is shown in FIGS. 5A-5C, the method 500 caninclude more or fewer steps or can arrange the order of the stepsdifferently than those shown in FIGS. 5A-5C. Further, two or more stepsmay be combined into one step. Generally, the method 500 starts with aSTART operation 504 and ends with an END operation 552. The method 500can be executed as a set of computer-executable instructions executed bya data-processing system and encoded or stored on a computer readablemedium. Hereinafter, the method 500 shall be explained with reference tothe systems, components, modules, software, data structures, userinterfaces, etc. described in conjunction with FIGS. 1-4 and 6-9.

Method 500 includes a capacity factor process described in FIG. 5A, aDelta-P loss process described in FIG. 5B and a ramp rate processdescribed in FIG. 5C. Method 500 may begin at step 504 and proceed tostep 508, where the compensation system 400 retrieves the rated capacityfor each inverter. The rated capacity for each inverter is retrieved bycompensation system 400 from the metadata stored in a database such asdata database 412, preferences databased 436 and/or analysis database456.

After retrieving the rated capacity for each inverter from the metadatafrom data database 412 for example at step 508, method 500 proceeds tostep 512, where the compensation system 400 retrieves the output powermeasurement value from each of the sensors for each of the inverters.The output power measurement value from each of the sensors may bestored individually and also as a sum of each of the output powermeasurement values, for example, in a database such as data database412, preferences databased 436 and/or analysis database 456.

After retrieving the output power measurement value from each of thesensors for each of the inverters at step 512, method 500 proceeds tostep 516, where the compensation system 400, using for example thecompensation analysis server 448 or the compensation analysis engine452, determines which inverters are ON based on stored data related toeach of the inverters. The stored data is, for example, data related tothe analysis conditions 440 and the performance thresholds 444 alongwith metadata from the sensors to determine which of the inverters hasan ON operating state and stored in a database such as data database412, preferences databased 436 and/or analysis database 456.

After determining which inverters are ON at step 516, method 500proceeds to step 520, where the compensation system 400 receives the POIoutput power measurement value for the PV power plant. The compensationsystem 400 receives the POI output power measurement value for the PVpower plant from a metering device such as the meter 353 for example. Asdiscussed in greater detail below, the POI output power measurementvalue for the PV power plant at step 520 is different than the outputpower measurement value from the sum of each of the sensors for each ofthe inverters at step 512.

After receiving the POI output power measurement value for the PV powerplant at step 520, method 500 proceeds to step 524, where thecompensation system 400 retrieves the power reference value for the PVpower plant. The power reference value for the PV power plant is, forexample, stored as metadata in a database such as data database 412,compensation database 456, preferences database 436 and/or any otherstorage facility.

After retrieving the power reference value for the PV power plant atstep 524, method 500 proceeds to step 528, where the compensation system400, using for example the compensation analysis server 448 and/or thecompensation analysis engine 452, determines a POI measured setpoint forthe PV power plant based on a difference between the power referencevalue for the PV power plant retrieved in step 524 and the received POIoutput power measurement value for the PV power plant at step 520.

After determining the POI measured setpoint for the PV power plant atstep 528, method 500 proceeds to step 532, where the compensation system400, using for example the compensation analysis server 448 and/or thecompensation analysis engine 452, calculates a capacity factor for theON inverters. The capacity factor for the ON inverters is based on therated capacity of the ON inverters divided by the total rated capacity.

The capacity factor is determined in equation (1) which provides thefollowing:

$\begin{matrix}{{{Capacity}\mspace{14mu}{Factor}} = \frac{\left( {{ON}\mspace{14mu}{Inverters}} \right)*\left( {{Rated}\mspace{14mu}{Capacity}} \right)}{\left( {{Total}\mspace{14mu}{Number}\mspace{14mu}{of}\mspace{14mu}{Inverters}} \right)*\left( {{Rated}\mspace{14mu}{Capacity}} \right)}} & (1)\end{matrix}$

wherein the ON inverters represent a subset of the total capacity andthe total number of inverters represent a total capacity. The lossassociated with a less than unity capacity factor, is determined byequation (2) which provides the following:

P _(loss)=Rated Capacity*(1−Capacity Factor)+C _(loss)  (2)

Where, C_(loss), is an additional loss component caused by controlsystem elements saturating prematurely but is not directly proportionalto the capacity factor. The value of C_(loss), depends on the capacityfactor and other predetermined control thresholds. When an inverter isON, its capacity is said to be available. By determining the capacityfactor and using it to adjust setpoint calculations and measurementfeedback throughout the control system as discussed in greater detailbelow, C_(loss), the additional loss component is significantly reduced.Thus, energy/revenue associated with the lost production is negated.

According to an alternative embodiment of the present disclosure, thecapacity factor may be determined based on whether or not the inverterremains in communication with the compensation system 400. If theinverter is no longer in communication with the compensation system 400,then the previous reading for the inverter is used. The previous readingmay be the reading before the inverter is no longer in communicationwith the compensation system 400. According to the alternativeembodiment of the present disclosure, the capacity factor may also bedetermined in equation (3) which provides the following:

$\begin{matrix}{{{Capacity}\mspace{14mu}{Factor}} = {{\left( {{\left( {{ON}\mspace{14mu}{{Inverters}/{Communicating}}\mspace{14mu}{Inverters}} \right)*\left( {{Rated}\mspace{14mu}{Capacity}} \right)} + {\sum\left( {{Not}\mspace{14mu}{Communicating}\mspace{14mu}{Inverters}\mspace{14mu}{Most}\mspace{20mu}{Recent}\mspace{14mu}{Output}\mspace{14mu}{Power}\mspace{14mu}{Measurement}\mspace{14mu}{Value}} \right)}} \right)/\left( {{Total}\mspace{14mu}{Number}\mspace{14mu}{of}\mspace{14mu}{Inverters}} \right)}*\left( {{Rated}\mspace{14mu}{Capacity}} \right)}} & (3)\end{matrix}$

After calculating the capacity factor for the ON inverters usingequation 1 or equation 3 at step 532, method 500 proceeds to step 536,where the compensation system 400, using for example the compensationanalysis server 448 and/or the compensation analysis engine 452,calculates an output power measurement value for the ON inverters.

After calculating the output power measurement value for the ONinverters at step 536, method 500 proceeds to step 540, where thecompensation system 400, using for example the compensation analysisserver 448 and/or the compensation analysis engine 452, calculates anadjusted POI measurement setpoint for the PV power plant which will bereferred to as the Setpoint.

After calculating an adjusted POI measurement setpoint for the PV powerplant at step 540, method 500 proceeds to step 544, where thecompensation system 400, using for example the compensation analysisserver 448 and/or the compensation analysis engine 452, assigns theadjusted POI measured setpoint to each of the ON inverters.

After assigning the adjusted POI measured setpoint to each of the ONinverters at step 544, method 500 proceeds to decision step 548, wherethe compensation analysis server 448 and/or the compensation analysisengine 452 determines whether or not the power reference value for thePV power plant retrieved in step 524 has been reached. If the powerreference value for the PV power plant has been reached (YES) indecision step 548, method 500 ends at END operation 552. If the powerreference value for the PV power plant has not been reached (NO) indecision step 548, method 500 proceeds to step 556, where thecompensation system 400, using for example the compensation analysisserver 448 and/or the compensation analysis engine 452, classifies eachON inverter as a TRACKING ON inverter or a NON-TRACKING ON inverter. Ifthe ON inverter is TRACKING, method 500 proceeds to the Delta-P lossprocess for TRACKING ON inverters which begins at step 560 of FIG. 5Band if the ON inverter is NON-TRACKING, method 500 proceeds to the ramprate process for NON-TRACKING ON inverters which begins at step 590 ofFIG. 5C.

TRACKING ON inverters are defined as ON inverters that operate at theSetpoint. Alternatively, NON-TRACKING ON inverters are defined as ONinverters that are unable to operate within a predetermined thresholdand a predetermined period of time of the Setpoint. At any time, aninverter operating within a PV power plant can encounter environmentallycaused constraints, causing the potential capacity of the PV power plantto fluctuate. Common factors contributing to the environmentally causedconstraints include irradiance, temperature, snow, soiling, etc. Thedistribution of the impact provided by the environmentally causedconstraints does not necessarily impact all ON inverters uniformly orchronologically and thus there is no preconceived priority given oroutcome expected from one inverter over another. The Delta-P lossprocess provides that the ON inverters that are unimpacted byenvironmentally caused constraints (TRACKING ON inverters) compensatefor inverters that are impacted by the environmentally causedconstraints (NON-TRACKING ON inverters). This is possible by taking themeasurements from sensors 350 at each inverter.

Referring to FIG. 5B, after classifying that an ON inverter is TRACKINGat step 556, method 500 proceeds to step 560, where the compensationsystem 400 retrieves the rated capacity for the TRACKING ON inverters.The rated capacity for the TRACKING ON inverters is retrieved bycompensation system 400 from the metadata stored in a database such asdata database 412, preferences databased 436 and/or analysis database456.

After retrieving the rated capacity for the TRACKING ON inverters atstep 560, method 500 proceeds to step 564, where the compensation system400, using for example the compensation analysis server 448 and/or thecompensation analysis engine 452, calculates a Delta-P loss for theTRACKING ON inverters. A current control cycle, n, is defined byequation (4) as follows:

Delta-P _(n) loss=Setpoint_(n)−Σ(Output Power Measurement Value for EachInverter_(n))   (4)

After calculating the Delta-P loss for the TRACKING ON inverters at step564, method 500 proceeds to step 568, where the compensation system 400,using for example the compensation analysis server 448 and/or thecompensation analysis engine 452, calculates a deviation percentage fromthe Delta-P loss. The deviation percentage is calculated in equation (5)as follows:

Deviation Percentage_(n)=Delta-P _(n) loss/Rated Capacity for theTRACKING ON inverters_(n)  (5)

After calculating the deviation percentage at step 568, method 500proceeds to step 572, where the compensation system 400, using forexample the compensation analysis server 448 and/or the compensationanalysis engine 452, adds the deviation percentage to the Setpoint forthe TRACKING ON inverters to generate an adjusted setpoint, referred toas the Adjusted Setpoint. The compensation system 400 adds the deviationpercentage calculated in step 568 to a new control cycle. According toan embodiment of the present disclosure, the deviation percentage isadded to the previous setpoint of the TRACKING ON inverters of theprevious control cycle as shown in equation (6) provided below.

Adjusted Setpoint,_(n)=Setpoint,_(n)+Deviation Percentage_(n)  (6)

In a physical sense, this loss or Delta-P loss is created bydisturbances (e.g. variable irradiance, soiling, snow) and can takeplace rapidly or slowly over time. These disturbances are referred to aslosses because their impact incurs a loss in instantaneous powerproduction. When integrated over time these Delta-P losses accumulateinto non-negligible losses in energy/revenue if the Delta-P loss is notused.

After adding the deviation percentage to the Setpoint for the TRACKINGON inverters to generate the adjusted setpoint at step 572, method 500proceeds to step 576, where the compensation system 400, using forexample the compensation analysis server 448 and/or the compensationanalysis engine 452, applies the adjusted setpoint to the TRACKING ONinverters.

After applying the adjusted setpoint to the TRACKING ON inverters atstep 576, method 500 proceeds to decision step 580 where thecompensation system 400, using for example the compensation analysisserver 448 and/or the compensation analysis engine 452, determines if aTRACKING ON inverter becomes NON-TRACKING. If a TRACKING ON inverterbecomes NON-TRACKING (YES) at decision step 580, method 500 proceeds tothe ramp rate process for NON-TRACKING ON inverters which begins at step590 of FIG. 5C.

If a TRACKING ON inverter does not become NON-TRACKING (NO) at decisionstep 580, method 500 proceeds to decision step 584 where thecompensation system 400, using for example the compensation analysisserver 448 and/or the compensation analysis engine 452, determines ifthe TRACKING ON inverter is outputting at the rated capacity. If theTRACKING ON inverter is outputting at the rated capacity (YES) atdecision step 584, method 500 returns to step 576, where thecompensation system 400, using for example the compensation analysisserver 448 and/or the compensation analysis engine 452, applies theadjusted setpoint to the TRACKING ON inverters. If the TRACKING ONinverter is not outputting at the rated capacity (NO) at decision step584, method 500 proceeds to decision step 588, where the compensationsystem 400, using for example the compensation analysis server 448and/or the compensation analysis engine 452 determines if the powerreference value for the PV power plant has been reached. If the powerreference value for the PV power plant has been reached (YES) atdecision step 588, method 500 returns to END operation 552. If the powerreference value for the PV power plant has not been reached (NO) atdecision step 588, method 500 returns to step 564 where the compensationsystem 400, using for example the compensation analysis server 448and/or the compensation analysis engine 452, calculates the Delta-P lossfor the TRACKING ON inverters.

According to an embodiment of the present disclosure, the AdjustedSetpoint is distributed among the TRACKING ON inverters. After theAdjusted Setpoint has been calculated, the process is implementedcontinuously and loops until any one of the following predeterminedconditions are met: 1) the TRACKING ON inverters undergo a disturbanceand thus are no longer TRACKING and are incorporated within theNON-TRACKING ON inverter group; 2) the TRACKING ON inverters areoutputting at their rated capacity; or 3) the power reference value forthe PV power plant has been reached. In conventional control systems,Delta-P losses are not considered. With Delta-P losses not beingconsidered, conventional PV power plant controllers artificially de-rateTRACKING ON inverters as the initial power drops at the POI. This rulesout complete compensation for traditional controllers that broadcastlimits to TRACKING ON inverters based upon POI feedback only. Accordingto embodiments of the present disclosure, by also measuring the outputpower for each of the ON inverters with the sensors 350 and thenclassifying each ON inverter as either a TRACKING ON inverter or aNON-TRACKING ON inverter leads to optimized control signals whereavailable. Thus, rather than providing a broadcast signal (i.e., asignal with only one magnitude at a given time), unique control signalscan be generated for every inverter at a given time when necessary.Therefore, this eliminates the need to provide a broadcast signal toeach inverter indiscreetly.

Now that the capacity factor process and the Delta-P loss process havebeen accounted for with the TRACKING ON inverters, method 500 proceedsto the ramp rate process which optimizes the recovery of theNON-TRACKING ON inverters as illustrated in FIG. 5C. Referring to FIG.5C, after classifying that an ON inverter is NON-TRACKING at step 556 inFIG. 5A or determining that a TRACKING ON inverter become a NON-TRACKINGON inverter at step 580 in FIG. 5B, method 500 proceeds to step 590,where the compensation system 400, using for example the compensationanalysis server 448 and/or the compensation analysis engine 452,corrects the adjusted POI measured Setpoint for each of the NON-TRACKINGON inverters to generate a Corrected Setpoint. The adjusted POI measuredSetpoint for each of the NON-TRACKING ON inverters is corrected by usingthe retrieved output power measurement value for each of the inverterfrom step 512 and multiplying it by 1+threshold percent as illustratedin equation (7) below:

Corrected Setpoint_(n)=Output Power Measurement Value_(n−1)*(1+ThresholdPercent)  (7)

where the threshold percent is a predetermined percentage value.

After the adjusted POI measured Setpoint for each of the NON-TRACKING ONinverters has been corrected at step 590, method 500 proceeds to step591, where the compensation system 400 retrieves the rated capacity forthe NON-TRACKING ON inverters. The rated capacity for the NON-TRACKINGON inverters is retrieved by compensation system 400 from the metadatastored in a database such as data database 412, preferences databased436 and/or analysis database 456.

After retrieving the rated capacity for the NON-TRACKING ON inverters atstep 591, method 500 proceeds to step 592, where the compensation system400, using for example the compensation analysis server 448 and/or thecompensation analysis engine 452, calculates a rate limited setpointincrease for the NON-TRACKING ON inverters. The rate limited setpointincrease is a derived value which is dependent on the sum of thecapacities of the NON-TRACKING ON inverters. The value is inverselyproportional to the number of NON-TRACKING ON inverters. This inverserelationship ensures that the rate of recovery for the NON-TRACKING ONinverters is optimized to recover as quickly as possible withoutviolating the POI rate limit. Therefore, as the number of NON-TRACKINGON inverters gets smaller, the rated rate limited setpoint increase getslarger. This is achieved conceptually as provided in equation (8):

Rate Limited Setpoint Increase_(n)=Constant Rate Limited SetpointIncrease/(Rated Capacity of NON-TRACKING ON inverters)_(n).  (8)

Therefore, the Corrected Setpoint for the NON-TRACKING ON inverters forthe next control cycles results in equation (9) which provides thefollowing:

Corrected Setpoint_(n+1)=Corrected Setpoint_(n)+Rate Limited SetpointIncrease_(n)  (9)

According to an alternative embodiment of the present disclosure, therate limited setpoint increase is calculated not only based on thecapacity of NON-TRACKING ON inverters as discussed above, but alsoincludes a dynamic rate limited setpoint increase component which isdiscussed in greater detail below. Equation (10) provides the ratelimited setpoint increase based on the dynamic rate limited setpointincrease component as follows:

Rate Limited Setpoint Increase_(n)=(Constant Rate Limited SetpointIncrease+Dynamic Rate Limited Setpoint Increase)/(Rated Capacity ofNON-TRACKING ON inverters)_(n)  (10)

The dynamic rate limited setpoint increase is calculated frommeasurements, taken from the POI meter 353. For example, two samples,separated by T seconds, are taken from the meter 353. The differencebetween the two samples is computed, resulting in the measurement ofDelta-P-T. Delta-P-T is the POI ramp rate over the period T, measured inthe units %/T seconds. Next, the POI ramp rate Delta-P-T is compared toan Ideal Delta-P-T which may be stored for example in metadata. Thedifference between Ideal Delta-P-T and POI ramp rate Delta-P-T is thedynamic rate limited setpoint increase. This optimization allowsNON-TRACKING ON inverters that have resources (e.g. irradiance) tocompensate for NON-TRACKING ON inverters without resources. TheNON-TRACKING ON inverters with resources, which cannot otherwisecompensate via the Delta-P loss because they are NON-TRACKING ONinverters, can now contribute more to optimizing energy harvest from thePV power plant.

The value of the rate limited setpoint increase using either equation(8) or equation (10) is optimized continuously based on the number ofNON-TRACKING ON inverters.

After calculating the rate limited setpoint increase for theNON-TRACKING ON inverters at step 592, method 500 proceeds to step 595,where the compensation system 400, using for example the compensationanalysis server 448 and/or the compensation analysis engine 452, addsthe calculated rate limited setpoint increase to the previous setpointto obtain an increased setpoint.

After the increased setpoint has been obtained at step 595, method 500proceeds to step 596, where the compensation system 400, using forexample the compensation analysis server 448 and/or the compensationanalysis engine 452, applies the increased setpoint to the NON-TRACKINGON inverters.

After applying the increased setpoint to the NON-TRACKING ON invertersat step 596, method 500 proceeds to decision step 597, where thecompensation system 400, using for example the compensation analysisserver 448 and/or the compensation analysis engine 452, determines if aNON-TRACKING ON inverter starts tracking at the adjusted setpoint as theTRACKING ON inverters. Due to the rate limited setpoint increase, theNON-TRACKING ON inverters are now tracking within a predetermined rangeof the TRACKING ON inverters and become TRACKING ON inverters.

If a NON-TRACKING ON inverter starts tracking (YES) at decision step597, method 500 proceeds to the Delta-P loss process for TRACKING ONinverters which begins at step 560 of FIG. 5B. If a NON-TRACKING ONinverter does not start tracking (NO) at decision step 597, method 500proceeds to decision step 598, where the compensation system 400, usingfor example the compensation analysis server 448 and/or the compensationanalysis engine 452, determines if the NON-TRACKING ON inverterexperiences a disturbance. If the NON-TRACKING ON inverter experiences adisturbance (YES) at decision step 598, method 500 returns to step 590,where the compensation system 400, using for example the compensationanalysis server 448 and/or the compensation analysis engine 452,corrects the adjusted POI measured setpoint for each of the NON-TRACKINGON inverters. If there is no disturbance with the NON-TRACKING ONinverter (NO) at decision step 598, method 500 proceeds to decision step599, where the compensation system 400, using for example thecompensation analysis server 448 and/or the compensation analysis engine452, determines if the power reference value for the PV power plant hasbeen reached. If the power reference value for the PV power plant hasbeen reached (YES) at decision step 599, method 500 returns to ENDoperation 552. If the power reference value for the PV power plant hasnot been reached (NO) at decision step 599, method 500 returns to step591 where the compensation system 400 retrieves the rated capacity forthe NON-TRACKING ON inverters.

According to an embodiment of the present disclosure, the value of therate limited setpoint increase is optimized continuously based on thenumber of NON-TRACKING ON inverters. The NON-TRACKING ON invertersincrease their power output so they become TRACKING ON inverters.Therefore, a recovery setpoint is continuously increased by the ratelimited increase amount. Method 500 continues where the process isimplemented continuously and loops until any one of the followingpredetermined conditions are met: (1) the output of NON-TRACKING ONinverters has increased sufficiently and is within a predeterminedpercentage magnitude for a predetermined amount of time, thus, theclassification of the NON-TRACKING ON inverter(s) moves fromNON-TRACKING to TRACKING; (2) the NON-TRACKING ON inverters undergo anew environmental constraint which results in a new Delta-P loss suchthat the NON-TRACKING ON inverter retains its NON-TRACKINGclassification and begins the sequence of correction of the setpoint; or(3) the power reference value for the PV power plant has been reached.

FIG. 6 is a block diagram of an embodiment of a capacity factor module600 according to the present disclosure. As described above, modules maybe a computer readable medium with functionality associated with aparticular task. The capacity factor module 600 according to the presentdisclosure includes three inputs and two outputs. The three inputsinclude a POI measured setpoint input 604 (the POI measured setpoint forthe PV power plant as discussed above in step 528), a sum of theoutpower measurement values input 608 (the sum of the power measurementvalues for each inverter as discussed above in step 512) and the ratedcapacity of the ON inverters input 612 (the numerator in equation 1 asdiscussed above). The two outputs include an adjusted POI measuredsetpoint output 616 (the adjusted POI measured setpoint for the PV powerplant discussed above in step 540) and an output power measurement valuefor ON inverters output 620 (the output power measurement value for theON inverters as discussed above in step 536). Using the data signals onthe inputs and referencing internal data from preferences andperformance thresholds, the capacity factor module 600 computes therespective outputs.

The following example provides an explanation for determining thecapacity factor for the ON inverters and the output power measurementvalue for the ON inverters using capacity factor module 600.

-   -   1. Assume the total number of inverters is 10    -   2. Assume the number of ON inverters is 8    -   3. Assume each inverter of the total number of inverters has a        rated capacity of 100    -   4. This means that the total rated capacity=1000 (100*10) and        rated capacity for the ON inverter=800 (100*8)    -   5. Therefore, the capacity factor for the ON        inverters=(8*100)/(10*100)=0.8 (by using equation 1 above)    -   6. Now assume that the POI output measurement value for the PV        power plant is 50% of total rated capacity    -   7. Since there are only 8 ON inverters, the output power        measurement value for the ON inverters)=50%/capacity        factor=50%/0.8=62.5%        The system produces 50% of the total rated power with only 80%        or 8 out of 10 of the ON inverters. Therefore, the ON inverters        aren't producing at 50%, they are actually producing at 62.5%.

FIG. 7 is a block diagram of an embodiment of a PV plant module 700according to the present disclosure. The PV plant module 700 includesthree inputs and one output. The three inputs include a power referencevalue input 704 (the power reference value of the PV power plantdiscussed above in step 524), a POI output measurement value input 708(the POI output measurement value for the PV power plant discussed abovein step 520), and a POI rate limit input 712 (the maximum increase ordecrease in power per unit time allowed at the POI). The single outputincludes a POI measured setpoint output 716 (the POI measured setpointfor the PV power plant as discussed above in step 528). Using the datasignals on the inputs and referencing internal data from preferences andperformance thresholds, the PV plant module 700 computes the singleoutput 716

FIG. 8 is a block diagram of an embodiment of a PV compensation module800 according to the present disclosure. The PV compensation module 800according to the present disclosure includes five inputs and twooutputs. The five inputs include an adjusted POI measured setpoint input804 (the adjusted POI measured setpoint for the PV power plant discussedabove in step 540), an input 808 for the output power measurement value(the output power measurement value for the ON inverters as discussedabove in step 536), a rated capacity of the ON inverters input 812 (thenumerator in equation 1 as discussed above), a rate capacity of TRACKINGON inverters input 816 (the rated capacity for the TRACKING ON invertersas discussed above in step 560) and a POI measurement ramp rate valueinput 820 (the POI measured ramp rate value as discussed above in step592). The two outputs include an adjusted setpoint output 824 (theadjusted setpoint applied to the TRACKING ON inverter as discussed instep 576) and a rate limited setpoint increase output 828 (the ratelimited setpoint increase as discussed in step 592). Using the datasignals on the inputs and referencing internal data from preferences andperformance thresholds, the PV compensation module 800 computes therespective outputs.

FIG. 9 is a block diagram of an embodiment of a PV unit module 900according to the present disclosure. The PV unit module 900 according tothe present disclosure includes three inputs and two outputs. The threeinputs include an input 904 for the adjusted setpoint applied to theTRACKING ON inverters (the adjusted setpoint applied to the TRACKING ONinverters as discussed above in step 576), a rate limited setpoint input908 (the calculated rate limited setpoint increase as discussed above instep 592) and an input 912 for the output power measurement value foreach inverter (the output power measurement value for each inverter asdiscussed above in step 512). The two outputs include a TRACKINGsetpoint output 916 (as discussed above in step 572) and a NON-TRACKINGsetpoint output 920 (as discussed above in step 596).

The PV unit module 900 is used to determine whether an ON inverter is aTRACKING ON inverter or a NON-TRACKING ON inverter. If the ON inverteris classified as a TRACKING ON inverter, then the PV unit module 900 atoutput 916 outputs the value received at 904 which represents thesetpoint sent to the TRACKING ON inverter. If the ON inverter isclassified as a NON-TRACKING ON inverter the PV unit module 900 atoutput 920 would either output the corrected setpoint plus the input at908 which is rate limited setpoint increase or the previous value atinput 908 (which is the previous rate limited setpoint increase).

The foregoing discussion has been presented for purposes of illustrationand description. The foregoing is not intended to limit the disclosureto the form or forms disclosed herein. In the foregoing DetailedDescription for example, various features of the present disclosure aregrouped together in one or more aspects, embodiments, and/orconfigurations for the purpose of streamlining the disclosure. Thefeatures of the aspects, embodiments, and/or configurations of thepresent disclosure may be combined in alternate aspects, embodiments,and/or configurations other than those discussed above. This method ofdisclosure is not to be interpreted as reflecting an intention that theclaims require more features than are expressly recited in each claim.Rather, as the following claims reflect, inventive aspects lie in lessthan all features of a single foregoing disclosed aspect, embodiment,and/or configuration. Thus, the following claims are hereby incorporatedinto this Detailed Description, with each claim standing on its own as aseparate embodiment of the present disclosure.

The present disclosure, in various aspects, embodiments, and/orconfigurations, includes components, methods, processes, systems and/orapparatus substantially as depicted and described herein, includingvarious aspects, embodiments, configurations embodiments,subcombinations, and/or subsets thereof. Those of skill in the art willunderstand how to make and use the disclosed aspects, embodiments,and/or configurations after understanding the present disclosure. Thepresent disclosure, in various aspects, embodiments, and/orconfigurations, includes providing devices and processes in the absenceof items not depicted and/or described herein or in various aspects,embodiments, and/or configurations hereof, including in the absence ofsuch items as may have been used in previous devices or processes, e.g.,for improving performance, achieving ease and\or reducing cost ofimplementation.

Although the present disclosure describes components and functionsimplemented in the aspects, embodiments, and/or configurations withreference to particular standards and protocols, the aspects,embodiments, and/or configurations are not limited to such standards andprotocols. Other similar standards and protocols not mentioned hereinare in existence and are considered to be included in the presentdisclosure. Moreover, the standards and protocols mentioned herein andother similar standards and protocols not mentioned herein areperiodically superseded by faster or more effective equivalents havingessentially the same functions. Such replacement standards and protocolshaving the same functions are considered equivalents included in thepresent disclosure.

Furthermore, it should be appreciated that the various links connectingthe elements can be wired or wireless links, or any combination thereof,or any other known or later developed element(s) that is capable ofsupplying and/or communicating data to and from the connected elements.These wired or wireless links can also be secure links and may becapable of communicating encrypted information. Transmission media usedas links, for example, can be any suitable carrier for electricalsignals, including coaxial cables, copper wire and fiber optics, and maytake the form of acoustic or light waves, such as those generated duringradio-wave and infra-red data communications.

Furthermore, while the exemplary aspects, embodiments, options, and/orconfigurations illustrated herein show the various components of thesystem collocated, certain components of the system can be locatedremotely, at distant portions of a distributed network, such as a LANand/or the Internet, or within a dedicated system. Thus, it should beappreciated, that the components of the system can be combined in to oneor more devices, such as a Personal Computer (PC), laptop, netbook,smart phone, Personal Digital Assistant (PDA), tablet, etc., orcollocated on a particular node of a distributed network, such as ananalog and/or digital telecommunications network, a packet-switchnetwork, or a circuit-switched network. It will be appreciated from thepreceding description, and for reasons of computational efficiency, thatthe components of the system can be arranged at any location within adistributed network of components without affecting the operation of thesystem. For example, the various components can be located in a switchsuch as a PBX and media server, gateway, in one or more communicationsdevices, at one or more users' premises, or some combination thereof.Similarly, one or more functional portions of the system could bedistributed between a telecommunications device(s) and an associatedcomputing device.

In the foregoing description, for the purposes of illustration, methodswere described in a particular order. It should be appreciated that inalternate embodiments, the methods may be performed in a different orderthan that described, and that changes, additions, and omissions to theorder of the methods can occur without materially affecting theoperation of the disclosed embodiments, configurations, and aspects ofthe present disclosure. It should also be appreciated that the methodsdescribed above may be performed by hardware components or may beembodied in sequences of machine-executable instructions, which may beused to cause a machine, such as a general-purpose or special-purposeprocessor or logic circuits programmed with the instructions to performthe methods. These machine-executable instructions may be stored on oneor more machine readable mediums, such as CD-ROMs or other type ofoptical disks, floppy diskettes, ROMs, RAMs, EPROMs, EEPROMs, magneticor optical cards, flash memory, or other types of machine-readablemediums suitable for storing electronic instructions. Alternatively, themethods may be performed by a combination of hardware and software.

Optionally, the systems and methods of this present disclosure can beimplemented in conjunction with a special purpose computer, a specialpurpose data-processing system, a programmed microprocessor ormicrocontroller and peripheral integrated circuit element(s), an ASIC orother integrated circuit, a digital signal processor, a hard-wiredelectronic or logic circuit such as discrete element circuit, aprogrammable logic device or gate array such as PLD, PLA, FPGA, PAL,special purpose computer, any comparable means, or the like. In general,any device(s) or means capable of implementing the methodologyillustrated herein can be used to implement the various aspects of thispresent disclosure. Exemplary hardware that can be used for thedisclosed embodiments, configurations and aspects includes computers,handheld devices, telephones (e.g., cellular, Internet enabled, digital,analog, hybrids, and others), and other hardware known in the art. Someof these devices include processors (e.g., a single or multiplemicroprocessors), memory, nonvolatile storage, input devices, and outputdevices. Furthermore, alternative software implementations including,but not limited to, distributed processing or component/objectdistributed processing, parallel processing, or virtual machineprocessing can also be constructed to implement the methods describedherein.

In yet another embodiment, the disclosed methods may be readilyimplemented in conjunction with software using object or object-orientedsoftware development environments that provide portable source code thatcan be used on a variety of computer or workstation platforms.Alternatively, the disclosed system may be implemented partially orfully in hardware using standard logic circuits or VLSI design. Whethersoftware or hardware is used to implement the systems in accordance withthis present disclosure is dependent on the speed and/or efficiencyrequirements of the system, the particular function, and the particularsoftware or hardware systems or microprocessor or microcomputer systemsbeing utilized.

In yet another embodiment, the disclosed methods may be partiallyimplemented in software that can be stored on a storage medium, executedon programmed general-purpose computer with the cooperation of acontroller and memory, a special purpose computer, a microprocessor, orthe like. In these instances, the systems and methods of this presentdisclosure can be implemented as program embedded on personal computersuch as an applet, JAVA® or CGI script, as a resource residing on aserver or computer workstation, as a routine embedded in a dedicatedmeasurement system, system component, or the like. The system can alsobe implemented by physically incorporating the system and/or method intoa software and/or hardware system.

Moreover, though the description has included description of one or moreaspects, embodiments, and/or configurations and certain variations andmodifications, other variations, combinations, and modifications arewithin the scope of the present disclosure, e.g., as may be within theskill and knowledge of those in the art, after understanding the presentdisclosure. It is intended to obtain rights which include alternativeaspects, embodiments, and/or configurations to the extent permitted,including alternate, interchangeable and/or equivalent structures,functions, ranges or steps to those claimed, whether or not suchalternate, interchangeable and/or equivalent structures, functions,ranges or steps are disclosed herein, and without intending to publiclydedicate any patentable subject matter. While the present disclosure hasbeen discussed with respect to various embodiments, it shall beunderstood that various other changes and modifications to the presentdisclosure can be made in accordance with the scope of the claimsappended hereto.

What is claimed is:
 1. A method of controlling a renewable energy powerplant, the method comprising: retrieving a sum of output powermeasurement values for each inverter of a total number of inverters froma plurality of sensors, with each sensor provided at a location proximalto each inverter; retrieving a point of interconnection (POI) outputmeasurement value for the renewable energy power plant based on aplurality of ON inverters of the total number of inverters; calculatinga POI measured setpoint for the renewable energy power plant based on adifference between a power reference value for the renewable energypower plant and the retrieved POI output measurement value for therenewable energy power plant; calculating a summation of output powermeasurement values for the ON inverters based on a capacity factor forthe ON inverters; calculating a setpoint for the renewable energy powerplant; assigning the setpoint to each of the ON inverters; andclassifying each ON inverter as either a TRACKING ON inverter or aNON-TRACKING ON inverter based on whether each ON inverter is trackingat the setpoint.
 2. The method of claim 1, further comprising increasingthe setpoint in response to detecting the summation of output powermeasurement values from each of the ON inverters is less than thesetpoint.
 3. The method of claim 1, further comprising: calculating aloss value for the TRACKING ON inverters; calculating a deviationpercentage from the loss value; and adding the deviation percentage tothe setpoint for the TRACKING ON inverters to generate an adjustedsetpoint.
 4. The method of claim 3, further comprising applying theadjusted setpoint to the TRACKING ON inverters until at least one of:the TRACKING ON inverters are no longer tracking and become NON-TRACKINGON inverters; the TRACKING ON inverters are outputting at their ratedcapacity; and the power reference value for the renewable energy powerplant has been reached.
 5. The method of claim 1, wherein the POI outputmeasurement value is retrieved from a meter provided between therenewable energy power plant and a power grid.
 6. The method of claim 1,further comprising correcting the setpoint for the NON-TRACKING ONinverters and adding a rate limited setpoint increase to theNON-TRACKING ON inverters.
 7. The method of claim 6, wherein the ratelimited setpoint increase is inversely proportional to a number ofNON-TRACKING ON inverters.
 8. A renewable energy power plant controller,the renewable energy power plant controller comprising a processor andmemory device, the renewable energy power plant controller configuredto: retrieve a sum of output power measurement values for each inverterof a total number of inverters from a plurality of sensors, with eachsensor provided at a location proximal to each inverter; retrieve apoint of interconnection (POI) output measurement value for a renewableenergy power plant based on a plurality of ON inverters of the totalnumber of inverters; calculate a POI measured setpoint for the renewableenergy power plant based on a difference between a power reference valuefor the PV power plant and the retrieved POI output measurement valuefor the renewable energy power plant; calculate a summation of outputpower measurement values for the ON inverters based on a capacity factorfor the ON inverters; calculate a setpoint for the renewable energypower plant; assign the setpoint to each of the ON inverters; andclassify each ON inverter as either a TRACKING ON inverter or aNON-TRACKING ON inverter based on whether each ON inverter is trackingat the setpoint.
 9. The renewable energy power plant controller of claim8, further configured to increase the setpoint in response to detectingthe summation of output power measurement values from each of the ONinverters is less than the setpoint.
 10. The renewable energy powerplant controller of claim 8, further configured to: calculate a lossvalue for the TRACKING ON inverters; calculate a deviation percentagefrom the loss value; and add the deviation percentage to the setpointfor the TRACKING ON inverters to generate an adjusted setpoint.
 11. Therenewable energy power plant controller of claim 10, further configuredto apply the adjusted setpoint to the TRACKING ON inverters until atleast one of: the TRACKING ON inverters are no longer tracking andbecome NON-TRACKING ON inverters; the TRACKING ON inverters areoutputting at their rated capacity; and the power reference value forthe renewable energy power plant has been reached.
 12. The renewableenergy controller of claim 8, wherein the POI output measurement valueis retrieved from a meter provided between the renewable energy powerplant and a power grid.
 13. The renewable energy controller of claim 8,further configured to correct the setpoint for the NON-TRACKING ONinverters and add a rate limited setpoint increase to the NON-TRACKINGON inverters.
 14. The renewable energy power plant controller of claim13, wherein the rate limited setpoint increase is inversely proportionalto a number of NON-TRACKING ON inverters.
 15. One or more non-transitorycomputer-readable storage media having computer-executable instructionsembodied thereon for controlling a plurality of renewable energyinverters, wherein when executed by a renewable energy power plantcontroller, the computer-executable instructions cause the renewableenergy power plant controller to: retrieve a sum of output powermeasurement values for each inverter of a total number of inverters froma plurality of sensors, with each sensor provided at a location proximalto each inverter; retrieve, from an electric meter, a point ofinterconnection (POI) output measurement value for a renewable energypower plant based on a plurality of ON inverters of the total number ofinverters; calculate a POI measured setpoint for the renewable energypower plant based on a difference between a power reference value forthe renewable energy power plant and the retrieved POI outputmeasurement value for the renewable energy power plant; calculate asummation of output power measurement values for the ON inverters basedon a capacity factor for the ON inverters; calculate a setpoint for therenewable energy power plant; assign the setpoint to each of the ONinverters; and classify each ON inverter as either a TRACKING ONinverter or a NON-TRACKING ON inverter based on whether each ON inverteris tracking at the setpoint.
 16. The computer-readable storage media ofclaim 15, wherein the computer-executable instructions also cause therenewable energy power plant controller to increase the setpoint inresponse to detecting the summation of output power measurement valuesfrom each of the ON inverters is less than the setpoint.
 17. Thecomputer-readable storage media of claim 15, wherein thecomputer-executable instructions also cause the renewable energy powerplant controller to: calculate a loss value for the TRACKING ONinverters; calculate a deviation percentage from the loss value; and addthe deviation percentage to the setpoint for the TRACKING ON invertersto generate an adjusted setpoint.
 18. The computer-readable storagemedia of claim 17, wherein the computer-executable instructions alsocause the renewable energy power plant controller to apply the adjustedsetpoint to the TRACKING ON inverters until at least one of: theTRACKING ON inverters are no longer tracking and become NON-TRACKING ONinverters; the TRACKING ON inverters are outputting at their ratedcapacity; and the power reference value for the renewable energy powerplant has been reached.
 19. The computer-readable storage media of claim15, wherein the computer-executable instructions also cause therenewable energy power plant controller to correct the setpoint for theNON-TRACKING ON inverters and add a rate limited setpoint increase tothe NON-TRACKING ON inverters.
 20. The computer-readable storage mediaof claim 19, wherein the rate limited setpoint increase is inverselyproportional to a number of NON-TRACKING ON inverters.